Abstract Microorganisms in nature are often found in porous confined environments (soils, sediments, or plant and animal tissues), self-organized in heterogeneous communities. Such an organization, resulting from complex interactions and self-generated steep chemical gradients, controls the emergent microbial community's ecological functions. The combination of microfluidics, fluorescent bacteria, and optical sensing can constitute a powerful tool to achieve new insights into these microbial dynamics. However, such a combination has remained challenging so far due to the limited compatibility of the current sensing approaches and fluorescent reporters. Here, we present a sensing microfluidic platform that enables simultaneous, real-time visualization of microscale oxygen gradients and multi-strain microbial community organization under flow. The approach combines transparent microfluidic devices, genetically encoded fluorescent bacteria, and the latest generation of near-infrared (NIR) luminescent oxygen sensors. We demonstrate that NIR oxygen sensing allows interference-free mapping of oxygen concentrations alongside GFP and mScarlet-I-labeled bacteria. Applying this platform to a heterogeneous porous geometry, we track the co-development of oxygen gradients and spatial organization in a two-strain Pseudomonas community under flowing conditions. The two strains exhibit distinct microscale spatial patterns consistent with known shape-dependent attachment and growth dynamics, while inducing sharp oxygen gradient formation. This work establishes a broadly accessible experimental framework for quantitatively linking microbial self-organization to chemical microenvironments in real time. This platform is cost-effective, customizable, and adaptable to sense different analytes, while being compatible with a range of spectrometry techniques. Therefore, this methodology opens new avenues for investigating microscale ecological processes in soils, sediments, and other confined habitats.
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Giulia Ceriotti
University of Lausanne
Sergey M. Borisov
Graz University of Technology
ISME Communications
University of Lausanne
Graz University of Technology
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Ceriotti et al. (Wed,) studied this question.
synapsesocial.com/papers/6a1bd0df5783ba022b6fc888 — DOI: https://doi.org/10.1093/ismeco/ycag146